Tunnel Lining Crack Recognition Based on Improved Multiscale Retinex and Sobel Edge Detection

Abstract

China is gradually transitioning from the “tunnel construction era” to the “tunnel maintenance era,” and more and more operating tunnels need to be inspected for diseases. With the continuous development of computer vision, the automatic identification of tunnel lining cracks with computers has gradually been applied in engineering. On the basis of summarizing the weaknesses and strengths of previous studies, this paper first uses the improved multiscale Retinex algorithm to filter the collected tunnel crack images and introduces the eight-direction Sobel edge detection operator to extract the edges of the cracks. Perform mathematical morphological operations on the image after edge extraction, and use the principle of the smallest enclosing rectangle to remove the isolated points of the image. Finally, the performance of the algorithm is judged by the objective evaluation index of the image, the accuracy of crack recognition, and the running time of the algorithm. The image filtering algorithm proposed in this paper can better preserve the edges of the image while enhancing the image. The objective evaluation indexes of the image have been improved significantly, and the main body of the crack can be accurately identified. The overall crack recognition accuracy rate can reach 97.5%, which is higher than the existing tunnel lining crack recognition algorithm, and the average calculation time for each image is shorter. This algorithm has high research significance and engineering application value.

Automatic image positioning of a rail train number using speed-up robust features and stroke width transform

“…The HSV + Sobel method 35 converts the rail train number images in the traditional RGB space into HSV color space, extracts the S channel, carries out Sobel operator edge detection, extracts the edge feature information, and combines the extracted feature information to extract the candidate region. Because the surface of the rail train is easy to rub with sand and stone under the condition of high-speed operation, resulting in the falling off of surface paint and small-scale color fluctuation.…”

Tunnel lining detection and retrofitting

“…Additionally, the proposed method can effectively eliminate interference, such as pipeline edges and strip marks, through multistage fusion filtering. Wang et al [49] proposed a method that combined the improved multiscale Retinex (MSR) algorithm for filtering and the eightdirection Sobel operator for edge extraction. A recognition rate of 97.5% was obtained and the processing efficiency of the algorithm was relatively high.…”